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Paavo Alku

Researcher at Aalto University

Publications -  452
Citations -  14648

Paavo Alku is an academic researcher from Aalto University. The author has contributed to research in topics: Speech processing & Linear prediction. The author has an hindex of 59, co-authored 433 publications receiving 13272 citations. Previous affiliations of Paavo Alku include Helsinki University of Technology & Johns Hopkins University Applied Physics Laboratory.

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Language-specific phoneme representations revealed by electric and magnetic brain responses

TL;DR: It is found that the brain's automatic change-detection response, reflected electrically as the mismatch negativity (MMN) was enhanced when the infrequent, deviant stimulus was a prototype relative to when it was a non-prototype (the Estonian /õ/).
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Glottal wave analysis with Pitch Synchronous Iterative Adaptive Inverse Filtering

TL;DR: The results show that the PSIAIF-algorithm is able to give a fairly accurate estimate for the glottal flow excluding the analysis of vowels with a low first formant that are produced with a pressed phonation type.
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Speech-sound-selective auditory impairment in children with autism: they can perceive but do not attend

TL;DR: The results demonstrate that, first, auditory orienting deficits in autism cannot be explained by sensory deficits and, second, that orienting deficit in autism might be speech–sound specific.
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Brain responses reveal the learning of foreign language phonemes.

TL;DR: The present study demonstrates the dynamic nature of cortical memory representations for phonemes in adults by using the mismatch negativity (MMN) event-related potential to study Hungarian and Finnish subjects and finds that the MMN for a contrast between two Finnish phoneme was elicited in the fluent Hungarians but not in the naive Hungarians.
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Normalized amplitude quotient for parametrization of the glottal flow

TL;DR: Comparison between NAQ and its counterpart among the conventional time-domain parameters, the closing quotient, shows that the proposed parameter is more robust against distortion such as measurement noise that make the extraction of conventionalTime-based parameters of the glottal flow problematic.